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Staff Product Manager, Machine Learning at Overstory

Overstory · On-site · Unspecified · Not listed

Posted · Rolepaper drops listings older than 30 days

Source: Arbeitnow

About this role

<div class="content-intro"><p>The climate crisis is the defining challenge of our time—but it’s also the greatest opportunity for innovation, and a challenge we’re proud to take on. At Overstory, we’re harnessing cutting-edge technology to enable a resilient electrical grid that keeps communities thriving as our world changes.</p> <p>The grid is the backbone of life as we know it. It powers hospitals, keeps food fresh, and ensures communities stay connected. But extreme weather, aging infrastructure, and growing wildfire risks are putting this critical system under pressure. All of this combined makes the electric utility industry the greatest opportunity for tackling climate change. </p> <p>One of the leading causes of catastrophic wildfires and power outages? Trees and brush coming into contact with power lines. </p> <p>That’s where we help. At Overstory, we use AI and advanced satellite imagery to pinpoint and prioritize vegetation risks before they materialize. By giving utilities critical analysis on those risks, we’re helping prevent outages, reduce wildfire risks, and accelerate the transition to a safer, more resilient grid.</p> <p>Our team spans the Americas and Europe, and we work with utility partners across the Americas and beyond. We’re outdoor enthusiasts, musicians, artists, athletes, parents, and adventurers. What unites us is a passion for solving complex problems, a commitment to climate action, and the belief that technology should be a force for good.</p> <p>Join us to help us build a more resilient world together. </p></div><h2><strong>Role & Team</strong></h2> <p>You’ll lead a core part of our Vegetation Intelligence, the product area that turns remote sensing imagery and data into the vegetation insights that utilities act on every day, through world-class machine learning models. It’s one of Overstory’s most foundational products, live with customers now, and it sits at the center of how we prevent outages and stop wildfires. Every missed tree is an outage or a fire that could have been prevented.</p> <p>The job is twofold. One is real ML-adjacent work: pushing our detection models further and turning their raw outputs into risk data precise enough for customers to trust and act on. You’ll need to be comfortable with complex machine learning models and geospatial data, close to the data science and engineering teams, and fluent enough in model trade-offs to make good calls with data scientists and ML engineers.</p> <p>The other side is where you get to build new capabilities: taking that same data and pushing it into new products and capabilities customers don't have yet. You'll run user research, ground new product bets in the decisions customers make in the field, and turn a strong model into products that prevent real fires and real outages.</p> <p>You’ll report to the Director of Product and own the strategy and roadmap for this product area end to end.</p> <p><strong>Time Zone Requirement:</strong> Europe (GMT/WET, CET, EET) and Eastern North America (NST, AST, EST, CST) Comfortable maintaining 3-4 hours of overlap European working hours for collaboration with the broader Overstory team.</p> <h2><strong>What You'll Do</strong></h2> <ul> <li>Own the roadmap for Vegetation Intelligence, spanning from the ML models that produce our risk data to the products that turn it into customer action.</li> <li>Push our detection models further, and help fold their outputs into Overstory’s broader outage and ignition risk models.</li> <li>Contribute towards increasing the number of actionable insights: run user research, ground priorities in the operational decisions customers actually make, and make sure what we ship drives real action in the field.</li&

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Is Rolepaper hiring for Staff Product Manager, Machine Learning?

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Posted Sat, 19 Sep 2026 07:55:05 GMT. Listings older than 30 days, or past the source expiry, are removed.